A sufficient condition for backtrack-bounded search
Journal of the ACM (JACM)
POPL '87 Proceedings of the 14th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
Constraint satisfaction problems in logic programming
ACM SIGART Bulletin
Constraint satisfaction in logic programming
Constraint satisfaction in logic programming
Enhancement schemes for constraint processing: backjumping, learning, and cutset decomposition
Artificial Intelligence
Communications of the ACM
Constraint relaxation may be perfect
Artificial Intelligence
The CLP( R ) language and system
ACM Transactions on Programming Languages and Systems (TOPLAS)
A generic arc-consistency algorithm and its specializations
Artificial Intelligence
Fast parallel constraint satisfaction
Artificial Intelligence
Decomposing constraint satisfaction problems using database techniques
Artificial Intelligence
Characterising tractable constraints
Artificial Intelligence
On the minimality and global consistency of row-convex constraint networks
Journal of the ACM (JACM)
Hierarchical neural network for rules control in knowledge-based expert systems
Neural, Parallel & Scientific Computations
Tractable constraints on ordered domains
Artificial Intelligence
Expert Systems: Principles and Programming
Expert Systems: Principles and Programming
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
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Knowledge-Based Expert Systems (KBES) have long been widely used to perform tasks that normally require human knowledge and intelligence. One important issue that has not been addressed satisfactorily in the existing KBESs is that they try to make posing queries simple by letting the users specify what they want to compute rather than how to compute it. In this paper, we show that the solutions computation process can be modeled with Constraint Satisfaction Problem (CSP) techniques, employing their simple representation schemes and consistency techniques. The motivation behind this is the desire to build up a computation model for reducing the vast amount of deductions required by a KBES when executed on a logic program system. A key idea is to represent the relations among the rules as constraints and to integrate the rule chaining with constraint solving. In this integration, the constraints are regarded as special facts at each node of the solutions graph, and the constraints propagation may cause firing of rules. In this way the model allows the solutions graph to grow progressively by enumerating the solutions of the system of constraints and validating the rules associated to these constraints. The approach to accomplish this is to spend more time in each node of the solutions graph by reducing the sets of possible values for not-yet-assigned variables. The model is introduced as a general control mechanism and realizes an a priori pruning in the solutions graph. This is done by assuming that the only rules to be considered are those arising from the propagation of their constraints and by computing only the rules that acquired some domain-dependent information about the significance of various domain interactions.